On Mon, 27 Dec 1999 17:44:51 +1000, "Greg Hooper"
<[EMAIL PROTECTED]> wrote:
> Thanks very much for that reply. The subjects are all 16 years old, right
> handed, equally split across sex etc, its a very homogenous group.
- From the whole post, it sounds as if you may be pretty satisfied
with your solution, and it seems fairly conventional from what I have
read.
But I can add a couple of observations that may pertain. Right here,
you say that it is a very homogeneous group. Do you consider the
consequences of that? -- every statement of reliability is a
statement about the measurement-in-that-sample. If your sample is not
hetergeneous in what you what to look for, correlational reliability
may be directing you to the wrong variables.
For in intraclass correlation, which is effectively what you computed,
you can compute the 2-way ANOVA, Subject by Time. The big F-test for
subjects shows that Subjects differ (reliably) on the measure. So,
how varied are the subjects? If *these* subjects are homogeneous on
what you want to detect -- when you do research later -- then what you
find to be reliable here might be something that distinguishes them
like sworls and ridges of fingerprints: unique, but of no inherent
meaning.
>
> The time
> effects are not significant because, due to a bunch of factors I won't go
> into, the time order of the measurements is randomised within each subject.
> ie you can't equate any order within one subject to the order of measurement
> within another subject. < ... snip, rest >
If there is a meaning to the type of measurements, then you certainly
*could* classify them by "Type" rather than time-period. When Type
corresponds to Treatments, varying the order of Treatments is the
basis of Crossover designs. Of course, you seemed to be just making a
side-comment here, so my observation might be irrelevant to your
purposes.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
